Abstract

As scholarly information increasingly gains attention as high-quality training data for artificial intelligence (AI), there is a growing interest in the Creative Commons (CC) licenses applied to academic publications. This study aims to analyze the determinants influencing the selection of CC licenses by Korean researchers for their academic papers. To this end, 3,320 open access articles published by Korean researchers in hybrid journals between 2020 and 2024 were selected for analysis. Cross-tabulation and chi-square tests were conducted to identify differences in CC license selection based on funding type, authorship composition, the corresponding author’s institutional affiliation type, academic discipline, and journal impact. Furthermore, a multinomial logistic regression analysis was performed to determine the specific effects of these variables. The results revealed that the inclusion of international co-authors increased the likelihood of adopting open CC licenses. Conversely, articles published in journals with higher impact factors showed a tendency toward more restrictive CC licenses. The findings of this study are expected to serve as foundational data for improving the CC licensing policies in South Korea and expanding the utilization of scholarly information as AI training data.